PowerPoint Presentation

Predictive Simulation ConferenceApril 28, 2016 MTC, Coventry, UKModelling and Improving the Environmental Impact of a Manufacturing System

D. Anagnostakis, J. M. Ritchie, T. Lim

OutlineIntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

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IntroductionThe companyProgress Rail Services (UK) Ltd.

Design and manufacture railway switches and crossings.

Crossing manufacture at South Queensferry plant.

Material: austenitic manganese steel.

Energy and carbon reduction pressures.

IntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

The objective of this study is the environmental impact assessment of a production system. Using appropriate indicators related to energy consumption and carbon emissions and discrete event simulation such as WITNESS, we can estimate the impacts from production processes on the environment.3

Case StudyAim

Environmental impact assessment of a production system within a manufacturing company.

Environmental performance indicators regardingenergy consumption & carbon emissions.

Discrete event simulation models using WITNESS predictive simulation software (Lanner Ltd., UK).

IntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

The objective of this study is the environmental impact assessment of a production system. Using appropriate indicators related to energy consumption and carbon emissions and discrete event simulation such as WITNESS, we can estimate the impacts from production processes on the environment.4

Manufacturing system Casting Heat Treatment Machine Shop Finishing department

Production of 10 crossing variants Similar geometry Different length and widthManufacturing System

IntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

The case study is based on a manufacturing company which produces equipment such as rails and railroad parts. The under investigation production system consists of three departments: heat treatment, machine shop and finishing focusing on the production of 10 different variants of casting crossings, which have similar geometry but different total length and width. 5

Heat Treatment

Charger:Loading1123Furnace:Heating21Quenching Tank:Cooling31Overhead CraneOverhead CraneStorage1Charger:Unloading1

The first section is the heat treatment department. In the figure the process flow of the crossings through this department appears. The crossings are loaded by an overhead crane on a charger which first loads the crossings in a furnace for heating at 1060 C. After this the crossings are quenched in a water tank, again using the charger. Finally the charger comes back to the initial position where the crossings are unloaded by the crane to a storage area.6

ForkliftMachine Shop

Press MachineFlattening bent crossings12x Milling MachineTop and Bottom surfacing2

123x CNC Milling MachineGeometry3StorageStorage2x Overhead CraneForklift3

233Overhead CraneLine 2Line 1

The other two parts of the production are the machine shop and the finishing department. The crossings are loaded in each work station by overhead cranes and unloaded from the machine shop to the finishing department using forklifts. The machine shop consists of a hydraulic press machine, two manual milling machines and 3 CNC milling machines. The finishing department includes three working stations where operators using hand held grinders remove any imperfections from the crossings surfaces.7

Finishing

StorageOverhead CraneForklift3x Finishing workstationsRemoving imperfections1111

The other two parts of the production are the machine shop and the finishing department. The crossings are loaded in each work station by overhead cranes and unloaded from the machine shop to the finishing department using forklifts. The machine shop consists of a hydraulic press machine, two manual milling machines and 3 CNC milling machines. The finishing department includes three working stations where operators using hand held grinders remove any imperfections from the crossings surfaces.8

Modelling

IntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

Production launchPeak demandEnd of production

To analyze and model the system at a detailed enough level, an input-output approach was used, taking into account parameters such as product demand, setup and process times.9

Power consumption modelling

Power consumption modelling

Modelling: Witness Model

Three distinct areas are included in the Witness model, Heat treatment, machine shop and finishing.For each component and machine the energy consumption of the greatest consumers has been modeled, such as fans, pumps and motors.12

Final WITNESS Model

Modelling components in WITNESSWITNESS - Part route SummaryWITNESS - Part file and Input structureWITNESS - Usage details reportWITNESS - Built-in graphs

WITNESS - Output variables

Simulation Scenario240 working days3 shifts x 7.5 working hours/shiftAnnual production volume: 800 crossingsProducts demand and variants:

IntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

The simulation period assumed to be 240 working days, 3 shifts with 7.5 h per shift. The total annual production volume is 800 crossings following this production mix for each one of the ten different variants of crossings.14

Simulation

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Results and discussionCurrent plant: Total energy consumption: 722.5 MWh Natural Gas provides 60% of total consumed energy

Total carbon emissions: 206 Tones CO2 Electricity causes 50% of total CO2 emissions

IntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

The final results from the simulation have indicated a total energy consumption of 722500 kwh and 206000 kg of CO2 emissions. We can observe that 60% of the total energy is provided by natural gas and half of the emissions are caused by the consumption of electricity. However to understand if these results are good or bad relative to the overall environmental performance of the system, the current system was compared to the ideal equivalent system which would have 100% of efficiency.16

Real plant vs. Ideal plantReal plant:

115% more energy consumption 98% more carbon emissions

All previous values based on real efficiency recalculated based on 100% efficiency for the components involved in each work station.

The results of the comparison indicated that the real system consumes 115 % more total energy than the ideal and emits 98% more CO2 during the production period.Thus it is obvious that there is a need for improvements from an energy consumption point of view.17

Optimisation Scenario

Benefits after replacement of furnace:

18% less energy consumption 14% less carbon emissions 28% cost reduction in natural gas

Another way to use this methodology is for assessing the performance of production systems when a component of the system (e.g. a milling machine or CNC) changes. In this case it was assumed that the furnace is replaced by another one 10 % more efficient than the old. The results show that the total energy consumption have been reduced by 18% while the total emissions have been reduced by 14 %.Moreover considering the average cost unit for natural gas, the purchase cost is calculated to be 28% less.18

ConclusionsModelling and simulation tools can contribute to:

Identification of high energy consuming components

Reduction of energy consumption and CO2 emissions

Increase in money savings

Enhanced decision making in environmental and production performance issues

Potential to be embedded in new product development process.

IntroductionCase studyManufacturing systemModellingSimulationResults and discussionConclusion

As a conclusion it can be said that by applying the proposed methodology combined with the discrete event simulation combined, high energy consuming areas or components within a production system can be identified leading to reduction of the energy consumption and carbon emissions and increase of money saving due to proper changes throughout the manufacturing system. Moreover this methodology can be extended to include further parameters and conditions relative to environmental or production performance issues, enhancing the process of decision making on these issues.19

Thank you for your attention

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ReferencesKalla D., Twomey J., Overcash M., Methodology for systematic analysis and improvement of manufacturing unit process life cycle inventory, 2010, Wichita State UniversityRajemi M. F., Energy Analysis in Turning and Milling, 2010, University of Manchester, School of Mechanical, Aerospace and Civil EngineeringTran K., Study of Electrical Usage and Demand at the Container Terminal, PhD Thesis, 2012, Deakin UniversityM.E. Eltantawie, Design, Manufacture and Simulate a Hydraulic Bending Press, 2013, Int. Journal of Mechanical Engineering and Robotics ResearchW. Trinks, M. H. Mawhinney, R. A. Shannon, R. J. Reedand J. R.Garvey, Industrial Furnaces,2004,John Wiley &Sons, IncRooda J. E., Vervoot J., Analysis of Manufacturing systems, 2005, Technische Universiteit Eindhoven, Department of Mechanical Engineering

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http://www.lanner.co.uk/